Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

A Bayesian scoring rule on clustered event data for familial risk assessment – An example from colorectal cancer screening

Colorectal cancer screening is well established. The identification of high risk populations is the key to implement effective risk‐adjusted screening. Good statistical approaches for risk prediction do not exist. The family's colorectal cancer history is used for identification of high risk families and usually assessed by a questionnaire. This paper introduces a prediction algorithm to designate a family for colorectal cancer risk and discusses its statistical properties. The new algorithm uses Bayesian reasoning and a detailed family history illustrated by a pedigree and a Lexis diagram. The algorithm is able to integrate different hereditary mechanisms that define complex latent class or random factor structures. They are generic and do not reflect specific genetic models. This is comparable to strategies in complex segregation analysis. Furthermore, the algorithm can integrate different statistical penetrance models for right censored event data. Computational challenges related to the handling of the likelihood are discussed. Simulation studies assess the predictive quality of the new algorithm in terms of ROC curves and corresponding AUCs. The algorithm is applied to data of a recent study on familial colorectal cancer risk. Its predictive performance is compared to that of a questionnaire currently used in screening for familial colorectal cancer. The results of the proposed algorithm are robust against different inheritance models. Using the simplest hereditary mechanism, the simulation study provides evidence that the algorithm improves detection of families with high cancer risk in comparison to the currently used questionnaire. The applicability of the algorithm goes beyond the field of colorectal cancer.     

Characterization of newly established colorectal cancer cell lines: correlation between cytogenetic abnormalities and allelic deletions associated with multistep tumorigenesis

We have established a series of 20 colorectal cancer cell lines and performed cytogenetic and RFLP analyses to show that the recurrent genetic abnormalities of chromosomes 1, 5, 17 and 18 associated with multistep tumorigenesis in colorectal cancer, and frequently detected as recurrent abnormalities in primary tumours, are also retained in long-term established cell lines. Earlier studies by us and other investigators showed that allelic losses of chromosomes 1 and 17 in primary colorectal cancers predicted poorer survival for the patients (P = 0.03). We utilized the cell lines to identify specific chromosomal sites or gene(s) on chromosomes 1 and 17 which confer more aggressive phenotype. Cytogenetic deletions of chromosome 1p were detected in 14 out of the 20 (70%) cell lines, whereas allelic deletions for 1p using polymorphic markers were detected in 13 out of 18 (72%) informative cell lines for at least one polymorphic marker. We have performed Northern blotting, immunohistochemical staining (p53 mRNA, protein) and RFLP analysis using several probes including p53 and nm23. RFLP analysis using a total of seven polymorphic markers located on 17p and 17q arms showed allelic losses aroundthe p53 locus in 16 out of the 20 cell lines (80%), four of which were losses of thep53 locus itself. In addition, seven cell lines (out of nine informative cases) also showed losses of thenm23 gene, four with concurrent losses of thep53 locus, while the remaining three were homozygous. In addition, five out of seven cell lines withnm23 deletions were derived from hepatic metastatic tumours, and one cell line was obtained from recurrent tumour. A comparison between allelic deletions of 1p and functional loss ofnm23 gene revealed a close association between these two events in cell lines derived from hepatic metastasis. Following immunohistochemical staining, nine out of the twenty cell lines showed high levels (25–80%) of mutant p53, four showed intermediate levels (>20%), and seven had undetectable levels of the protein. Of these seven, four showed complete absence of mRNA. Of the remaining three cell lines one showed aberrant mRNA due to germline rearrangement of thep53 gene, whereas in two cell lines normal levels of mRNA were present. Nineteen of the 20 cell lines had normal germline configurations for thep53 gene, while one showed a rearrangement. These data suggest that functional loss ofp53 andnm23 genes accomplished by a variety of mechanisms may be associated with poor prognosis and survival. In addition, concurrent deletions of chromosome regions 17p, 17q and 1p were closely associated with high-stage hepatic metastatic disease. These cell lines with well-characterized genetic alterations and known clinical history provide an invaluable source of material for various biological and clinical studies relating to multistep colorectal tumorigenesis.     

The Functional Repertoire of Survivin's Tails

Survivin is a multitasking protein that can inhibit cell death and that is essential for mitosis. Due to these prosurvival activities and the correlation of its expression with tumor resistance to conventional cancer treatments, survivin has received much attention as a potential oncotherapeutic target. Nevertheless, many questions regarding its exact role at the molecular level remain to be elucidated. In this study we ask whether the extreme C- and NH₂ termini of survivin are required for it to carry out its cytoprotective and mitotic duties. When assayed for their ability to act as a cytoprotectant, both survivin_1–120 and survivin_11–142 were able to protect cells against TRAIL-mediated apoptosis, but when challenged with irradiation cells expressing survivin_11–142 had no survival advantage. During mitosis, however, removing the NH₂ terminal 10 amino acids (survivin_11–142) had no apparent effect but truncating 22 amino acids from the C-terminus (survivin_1–120) prevented survivin from transferring to the midzone microtubules during anaphase. Collectively the data herein presented suggest that the C-terminus is required for cell division, and that the NH₂ terminus is dispensable for apoptosis and mitosis but required for protection from irradiation.     

Proteins in Tumor-Derived Plasma Extracellular Vesicles Indicate Tumor Origin

Cancer-derived extracellular vesicles (EVs) promote tumorigenesis, premetastatic niche formation, and metastasis via their protein cargo. However, the proteins packaged by patient tumors into EVs cannot be determined in vivo because of the presence of EVs derived from other tissues. We therefore developed a cross-species proteomic method to quantify the human tumor-derived proteome of plasma EVs produced by patient-derived xenografts of four cancer types. Proteomic profiling revealed individualized packaging of novel protein cargo, and machine learning accurately classified the type of the underlying tumor.     

Structural transition of kidney cystatin in dimethylnitrosamine-induced renal cancer in rats: identification as a novel biomarker for kidney cancer and prognosis

In our study, renal cancer is induced in rats making use of dimethylnitrosamine (DMN). G1 – Group 1 were control rats and G2 – Group 2 rats were given a single intra-peritoneal injection of DMN of 50 mg/kg body weight resulting in 100% incidences of renal tumors after 12 months. SEM and histopathology confirmed the presence of renal cancer in the DMN-treated rats. Making use of ammonium sulfate precipitation and gel filtration chromatography on Sephacryl S-100HR column, a thiol protease inhibitor was isolated from kidney of control rats known as Rat kidney Cystatin (RKC) as well as from kidney of cancerous rat called as Cancerous Rat Kidney Cystatin (CRKC). Both these inhibitors were characterized, and interestingly, it was found that CRKC showed greater anti-papain activity and also it was stable in a broad pH and temperature range thus implying that CRKC is more stable as compared to RKC. UV and fluorescence spectroscopy point out in structural difference between RKC and CRKC which was further confirmed by Circular dichroism (CD) and FTIR spectroscopy. Our study clearly showed that kidney cystatin is structurally modified in the case of renal cancer and performs its role in a more efficacious manner.     

Natural product pectolinarigenin exhibits potent anti-metastatic activity in colorectal carcinoma cells in vitro and in vivo

Colorectal carcinoma (CRC) is one of the most common cancers with high metastatic potential, explaining why identifying new drug candidates that inhibit tumour metastasis is an urgent need. The aim of this study was to evaluate the biological activities of pectolinarigenin (PEC, a natural flavonoid present in Cirsium chanroenicum) in CRC in vitro and in vivo and to determine its underlying mechanism of action. Here, we observed that treatment with PEC could inhibit cell viability and induce apoptosis in cancer cells in a concentration- and time-dependent manner. The occurrence of apoptosis was associated with activation of caspase-3 and Bax and decreased expression of Bcl-2. In addition, PEC markedly impaired CRC cell migration and invasion by downregulating the expression of matrix metalloproteinase (MMP-9) and phosphorylated-Stat3^Tyr705. Moreover, our studies showed that PEC inhibited abdominal metastasis models of murine colorectal cancer. In addition, histological and immunohistochemical analyses revealed a decrease in Ki67-positive cells, MMP9-positive cells and p-Stat3^Tyr705 cells upon treatment with PEC compared to control samples. Furthermore, PEC reduced the number of myeloid-derived suppressor cells (MDSCs) in the blood and tumours, which was accompanied by the increased infiltration of CD8⁺T cells in the blood. Taken together, our findings suggested that PEC could be used as a natural drug to inhibit CRC metastasis.